The image quality of a blurred image may be sharpened by processing a portion where the luminance is changed such as a boundary of a photogenic subject or a character, that is, an edge area of the image. For example, in JP-A 2007-310837 and “Reconstruction-based Super-resolution using self-congruency of images” Technical Report of Institute of Electronics Information and Communication Engineers, Institute of Electronics Information and Communication Engineers, December 2007, Volume 107, No. 379, CS 2007-52, p. 135-140 by Ida, Matsumoto, and Isogawa, whether it is an edge area or not is determined on the pixel to pixel basis on the image using Sobel operator (for example, see “Image processing engineering” by Ryoichi SUEMATSU and Hironao YAMADA, issued from Corona K. K, first edition, October 2000, p. 105) on an entered image as shown in FIG. 16. Then, when it is determined to be an edge area, a sharpening process referred to as Reconstruction-based Super-resolution is applied to a peripheral area thereof.
There are two types of Sobel operators. A first type is to detect an edge in the horizontal direction by inspecting the luminance difference between pixels above and below a pixel to be determined as shown in FIG. 6. A second type is to detect an edge in a vertical direction by inspecting the luminance difference between pixels on the left and right sides as shown in FIG. 7. Then, the Sobel operators carry out sum-of-product calculation on 3×3 pixels around the pixel to be determined with coefficients shown in FIG. 6 and FIG. 7. The Sobel operators determine whether the pixel to be determined is in the edge area or not using the output values therefrom.
In Ida et. al, the pixel to be determined is determined to be an edge area when the sum of absolute values of outputs of the two Sobel operators in the horizontal direction and the vertical directions is larger than a threshold value. For example, an edge detection results by the Sobel operators when an edge area as shown in FIG. 10 is entered are shown in FIG. 11. Round marks in FIG. 10 represent pixels, and the white color and the black color represent their luminance. In this example, the luminance is expressed in two tones for the simplicity. However, there is an intermediate luminance values in fact, and in such a case, the luminance value has 256 tones from 0 to 255. Squares in FIG. 11 represent positions which are determined to be the edge areas. In this manner, detection is achieved correctly along the actual edge area.
As described above, by using the Sobel operators, the edge areas of the image can be detected, and by applying image processing such as sharpening to the edge areas, the image quality is effectively improved.
However, when considering brightness changes with little differences in luminance as shown in FIG. 12, for example, there are edge areas of a length as short as about three pixels. Therefore, the Sobel operators detect these areas as the edge areas as shown in FIG. 13.
However, parts having many short edge areas in different directions are referred to as texture areas, and are not the boundaries of the photogenic subject or the characters. Therefore, these parts need not to be sharpened. These parts are parts which are not desired to be detected as the edge areas in terms of throughput saving. However, there is a problem that these parts are detected as the edge areas.